{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(sys.path[0]))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/data02/users/lz/miniconda3/envs/UICoder/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "os.environ['TOKENIZERS_PARALLELISM'] = 'True'\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "from PIL import Image,ImageDraw\n",
    "import easyocr\n",
    "import numpy as np\n",
    "import json\n",
    "import re\n",
    "import torch\n",
    "from tqdm import tqdm\n",
    "from scripts.train.utils import smart_tokenizer_and_embedding_resize,Html2BboxTree,move_to_device,BboxTree2Html,add_special_tokens\n",
    "from vars import *\n",
    "from my_dataset import UICoderDataset,UICoderCollater\n",
    "from transformers import AutoProcessor, Pix2StructForConditionalGeneration,AddedToken\n",
    "from utils import Html2BboxTree, BboxTree2StyleList, BboxTree2Html\n",
    "from datasets import Dataset\n",
    "\n",
    "torch.manual_seed(SEED)\n",
    "\n",
    "device = 'cuda:0'\n",
    "model_path = \"/data02/users/lz/code/UICoder/checkpoints/stage2/l256_p512_ws_1m*1/checkpoint-90000\"\n",
    "# data_path = '/data02/users/lz/code/UICoder/datasets/WebSight-format-parquet'\n",
    "data_path = '/data02/starmage/datasets/cc/arrows_8-14_processed/'\n",
    "output_dir = '/data02/users/lz/code/UICoder/test_result'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00,  1.37it/s]\n"
     ]
    }
   ],
   "source": [
    "processor = AutoProcessor.from_pretrained(processor_name_or_path)\n",
    "model = Pix2StructForConditionalGeneration.from_pretrained(model_path,is_encoder_decoder=True,device_map=device,torch_dtype=torch.float16)\n",
    "add_special_tokens(model, processor.tokenizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = Dataset.load_from_disk('/data02/users/lz/code/UICoder/datasets/WebSight-format-parquet/arrow')\n",
    "# ds = UICoderDataset(path=data_path,processor=processor,max_length=2048,max_patches=512,max_num=100,drop_longer=True,stage=1,preprocess=True, make_patches_while_training=True, workers=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1280, 720)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# image = Image.open('/data02/users/lz/code/image.jpg')\n",
    "image = ds[669]['image']\n",
    "image.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def parse_prediction(prediction, size=(1280,960)):\n",
    "    pieces = prediction.split('%')\n",
    "    ftype = pieces[0].split('<')[0]\n",
    "    fstyle = pieces[1]\n",
    "    fnode = {\n",
    "        'type': ftype,\n",
    "        'style': fstyle\n",
    "    }\n",
    "    \n",
    "    cnodes = list(filter(lambda x:x,pieces[0].split('<')[1].split('>')[0].split(')')))\n",
    "    cnodes = list(map(lambda x:{\n",
    "        'type': x.split('(')[0].replace(',',''),\n",
    "        'bbox': list(map(lambda x:float(x),x.split('(')[1].split(',')))\n",
    "    },cnodes))\n",
    "\n",
    "    for idx, node in enumerate(cnodes):\n",
    "        bbox = node['bbox']\n",
    "        node['bbox'] =  [int(bbox[0]*size[0]), int(bbox[1]*size[1]), int(bbox[2]*size[0]), int(bbox[3]*size[1])]\n",
    "\n",
    "    cstyles = ''.join(pieces[3:-1]).split(',')\n",
    "    for idx, style in enumerate(cstyles[:len(cnodes)]):\n",
    "        cnodes[idx]['style'] = style\n",
    "\n",
    "    fnode['children'] = cnodes\n",
    "\n",
    "    return fnode\n",
    "\n",
    "def drawBboxOnImage(draw: ImageDraw,bbox_node):\n",
    "    bbox = bbox_node['bbox']\n",
    "    if bbox[2] > 0 and bbox[3] > 0:\n",
    "        draw.rectangle((bbox[0],bbox[1],bbox[0]+bbox[2],bbox[1]+bbox[3]),outline=\"red\",width=2)\n",
    "    if 'children' in bbox_node:\n",
    "        for node in bbox_node['children']:\n",
    "            drawBboxOnImage(draw, node)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict(node, image):\n",
    "    model.eval()\n",
    "    with torch.no_grad():\n",
    "        input = node['type']\n",
    "        decoder_input_ids = processor.tokenizer.encode(input,return_tensors='pt',add_special_tokens=True)[...,:-1]\n",
    "        encoding = processor(images=[image],text=[\"\"],max_patches=512,return_tensors='pt')\n",
    "        item = {\n",
    "            'decoder_input_ids': decoder_input_ids,\n",
    "            'flattened_patches': encoding['flattened_patches'].half(),\n",
    "            'attention_mask': encoding['attention_mask']\n",
    "        }\n",
    "        item = move_to_device(item,device)\n",
    "\n",
    "        outputs = model.generate(**item,max_new_tokens=2048,eos_token_id=processor.tokenizer.eos_token_id,do_sample=True)\n",
    "\n",
    "        prediction = processor.tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]\n",
    "\n",
    "        pre_node = parse_prediction(prediction, (node['bbox'][2], node['bbox'][3]))\n",
    "\n",
    "        node['children'] = pre_node['children']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "root_node = {\n",
    "    'type': 'body',\n",
    "    'bbox': [0, 0, image.size[0], image.size[1]]\n",
    "}\n",
    "predict(root_node, image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for node in tqdm(root_node['children']):\n",
    "#     try:\n",
    "#         predict(node, image.crop((max(node['bbox'][0],0), max(node['bbox'][1],0), max(node['bbox'][0],0)+min(node['bbox'][2], image.size[0]), max(node['bbox'][1],0)+min(node['bbox'][3],image.size[1]))))\n",
    "#     except:\n",
    "#         print(1)\n",
    "#         pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'type': 'body',\n",
       " 'bbox': [0, 0, 1280, 720],\n",
       " 'children': [{'type': 'header',\n",
       "   'bbox': [0, 0, 1280, 86],\n",
       "   'style': 'box-sizing: border-box; background-color: #f8f8f8; padding: 10px'},\n",
       "  {'type': 'section',\n",
       "   'bbox': [0, 86, 1280, 86],\n",
       "   'style': 'box-sizing: border-box; border: 1px solid #000; padding: 10px'},\n",
       "  {'type': 'section',\n",
       "   'bbox': [0, 194, 1280, 57],\n",
       "   'style': 'box-sizing: border-box; border: 1px solid #000; padding: 10px'},\n",
       "  {'type': 'section',\n",
       "   'bbox': [0, 237, 1280, 144],\n",
       "   'style': 'box-sizing: border-box; display: flex; flex-wrap: wrap'}]}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "root_node"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=1280x720>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pImage = image.copy()\n",
    "drawBboxOnImage(ImageDraw.Draw(pImage),root_node)\n",
    "pImage"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
